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My dataset is about clients in arrears and contain the two following columns: cured which takes value 1 when the client cured and 0 otherwise, and self_cured which takes value 1 when client cured by themselves and 0 when they cured after being contacted. The dataset includes other behaviour and application variables as well.

I'm interested in studying the likelihood of a client in arrears to self cure. As you can see, there's a conditionality in my data: the self_cured variable is only relevant when the client cured (so, has a 1 in cured).

To account for this, I thought maybe I could do what I call a "two phase regression", that would look like this:

reg 1: cured ~ application_vars + behaviour_vars + u 

which will give the probability of cure aka the people that "will" cure

reg 2: self_cured ~  application_vars + behaviour_vars + s 

Where reg 1 would be a logistic regression run with the entire dataset and reg 2 just with the ones that were found cured from the first regression.

My question is, is there a name for this kind of thing? Do you have any sugestion about this?

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